| 1. |
- Holm, M., et al.
(author)
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A New Method for Analysis of Atrial Activation during Chronic Atrial Fibrillation in Man
- 1996
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In: IEEE Transactions on Biomedical Engineering. - : Institute of Electrical and Electronics Engineers (IEEE). - 1558-2531 .- 0018-9294. ; 43:2, s. 198-210
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Journal article (peer-reviewed)abstract
- To further clarify the mechanisms maintaining chronic atrial fibrillation (CAF), a method identifying preferable activation patterns of the atria during fibrillation, by time averaging of multiple discrete excitation vectors, was developed. Repeated recordings, each of 56 atrial bipolar electrograms simultaneously acquired during 8 s, were made at multiple sites in the right atrial free wall and the left atrial appendage in 16 patients with CAF using a 2.17/spl times/3.54 cm electrode array. The local activation times (LAT's) in each recording were estimated as the median activation time at the respective measurement point. By calculating the time difference between the LAT's at adjacent measurement points in two spatial dimensions, a direction vector was created for each activation wave passing each set of measurement points, a total of 42 sets. By time averaging of the individual direction vectors (typically n=55) at each set of measurement points, preferable activation patterns were determined. Three types of activation patterns were found: 1) inconsistent activation (n=5), 2) consistent activation with preferential propagation directions (n=7) and 3) consistent activation with impulses originating from a localizable site within the recording area (n=4). All activation patterns were reproducible and the two latter patterns were proven significant using statistical tests. It is concluded that this new method is useful in further clarification of the mechanisms involved in the maintenance of atrial fibrillation.
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| 3. |
- Karlsson, Stefan, et al.
(author)
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Enhancement of spectral analysis of myoelectric signals during static contractions using wavelet methods
- 1999
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In: IEEE Transactions on Biomedical Engineering. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9294 .- 1558-2531. ; 46:6, s. 670-684
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Journal article (peer-reviewed)abstract
- In this paper, we introduce wavelet packets as an alternative method for spectral analysis of surface myoelectric(ME) signals. Both computer synthesized and real ME signals are used to investigate the performance. Our simulation results show that wavelet packet estimate has slightly less mean squareerror (MSE) than Fourier method, and both methods perform similarly on the real data. Moreover, wavelet packets give us some advantages over the traditional methods such as multiresolutionof frequency, as well as its potential use for effecting time-frequency decomposition of the nonstationary signals such as the ME signals during dynamic contractions. We also introduce wavelet shrinkage method for improving spectral estimates bysignificantly reducing the MSE’s for both Fourier and wavelet packet methods.
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| 4. |
- Sandsten, Maria, et al.
(author)
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A system for tracking changes in the mid-latency evoked potential during anesthesia
- 1998
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In: IEEE Transactions on Biomedical Engineering. - : Institute of Electrical and Electronics Engineers (IEEE). - 1558-2531 .- 0018-9294. ; 45:3, s. 323-334
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Journal article (peer-reviewed)abstract
- Describes a method to measure changes in the mid-latency auditory evoked potential (MLAEP) during anesthesia. It is claimed that the position of the Nb-trough of the MLAEP indicates the level of consciousness. The component shows graded changes corresponding to the dose of anesthetic and it exhibits stable reproducible properties between different subjects. The authors propose a system that reduces the disturbances in an averaged MLAEP using fewer realizations than in the standard averaging procedure. The resulting smoothing error is reduced if the number of stimulus is decreased. Unfortunately, the variance of the waveform estimate is, thereby, increased. An improved method must be used in order to estimate the Nb-trough within a prescribed time interval of one minute. The procedure is based on inherent properties of the MLAEP and the noise. A simulation and examples of the performance on real data recorded during surgery are shown.
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| 5. |
- Sandsten, Maria, et al.
(author)
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Estimation of single event related potentials utilizing the Prony method
- 1996
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In: IEEE Transactions on Biomedical Engineering. - : Institute of Electrical and Electronics Engineers (IEEE). - 1558-2531 .- 0018-9294. ; 43:10, s. 973-981
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Journal article (peer-reviewed)abstract
- This paper deals with estimation of the waveform of a single event-related potential, sERP. An additive noise model is used for the measured signal and the SNR of the disturbed sERP is approximately 0 dB. The sERP is described by a series expansion where the basis functions are damped sinusoids. The fundamental basis function is estimated by the least squares Prony method, derived for colored noise. The performance of the Prony method for different forms of the power density spectrum of the noise is investigated. A white noise approximation can be used at low signal-to-noise (SNR). The basis functions change slowly but the waveform of the sERP may vary from one stimulus to another, thus the authors average a small number of correlation functions in order to increase the SNR. The method is evaluated by using measurements from four subjects and the results confirm the variability of the sERP.
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| 6. |
- Stokes, V P, et al.
(author)
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Dominant pattern extraction from 3-D kinematic data.
- 1999
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In: IEEE Transactions on Biomedical Engineering. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9294 .- 1558-2531. ; 46:1, s. 100-6
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Journal article (peer-reviewed)abstract
- A new method for the extraction of a repeating pattern in cyclic biomechanical data is proposed--singular value decomposition pattern analysis (SVDPA). This method is based on the recent work of Kanjilal and Palit [14], [15] and can be applied to both contiguous and repeated trials without being constrained to be strictly periodic. SVDPA is a data-driven approach that does not use a preselected set of basis functions; but instead utilizes a data matrix with a special structure to identify repeating patterns. Several important features of SVDPA are described including its close relationship to the Kahunen-Loève transform. The dominant pattern is defined as the average energy component (AEC). The AEC is obtained from the SVD of the data matrix and is equivalent to the optimal [maximal signal-to-noise ratio (SNR)] ensemble average pattern. The degree of periodicity and SNR for the AEC are defined explicitly from the singular values of the data matrix. We illustrate the usefulness of SVDPA for dominant pattern extraction by applying it to the quasiperiodic three-dimensional trajectory of a marker attached to the trunk during treadmill locomotion. The AEC obtained for the normalized trajectory and error estimates at each point suggests that SVDPA could be a useful tool for the extraction of the fine details from cyclic biomechanical data.
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